Embodiments relate generally to the field of circuit assembly manufacturing, and more particularly to tools for predicting circuit assembly yields with respect to component placement manufacturing processes.
Electronic devices and systems typically include at least one circuit assembly. The circuit assembly includes a number of circuit components (e.g., discrete components, integrated circuits, circuit sub-assemblies, etc.) that may be coupled to a carrier having conductive and/or non-conductive features (e.g., a printed circuit board (PCB) with traces). The circuit assembly can be manufactured using one or more of a number of different processes. For example, wave soldering, manual soldering, surface mount technology (SMT), and/or other processes can be used to populate electronic components onto a PCB or flexible substrate.
Particularly in high-volume or critical manufacturing applications, it is desirable to predict potential failures in the manufacturing of an electronic assembly that can impact overall product yield, including those attributable to component failures and those attributable to manufacturing process failures. However, yield prediction can be difficult for a number of reasons. For example, each component has various potential failure modes, and those failure modes can change with respect to which manufacturing process is being used to populate that component, where in the process the component is populated to the carrier, spacing and/or placement constraints placed on the component, and/or other design and manufacturing considerations. Further, as component counts increase, the possible failure scenarios for the circuit assembly can increase dramatically. Even further, costs associated with addressing (e.g., repairing or reworking) a failure can vary widely with respect to the types of failure that occurred, the type of component that failed, the type of manufacturing process used to populate that component, where in the process the failure occurred, etc.
Indeed, traditional yield prediction techniques fail to account for many of these factors and have tended to provide unreliable results. For example, many traditional techniques provide crude representations and/or groupings of the components being used in the circuit assembly (e.g., ignoring lead type, pitch, rotation, etc.) and do not account for the type of manufacturing process being used or screening techniques that may be available at different points in the manufacturing process. Further, traditional techniques typically do not account for feedback (e.g., from testing methodologies, actual factory yields, etc.) to tune yield predictions.